Closed circuit television (CCTV) is widely used for security, transport and other purposes. Example applications include the observation of crime or vandalism in public open spaces or buildings (such as hospitals and schools), intrusion into prohibited areas, monitoring the free flow of road traffic, detection of traffic incidents and queues, detection of vehicles travelling the wrong way on one-way roads.
The monitoring of CCTV displays (by human operators) is a very laborious task however and there is considerable risk that events of interest may go unnoticed. This is especially true when operators are required to monitor a number of CCTV camera outputs simultaneously. As a result in many CCTV installations, video data is recorded and only inspected in detail if an event is known to have taken place. Even in these cases, the volume of recorded data may be large and the manual inspection of the data may be laborious. Consequently there is a requirement for automatic devices to process video images and raise an alarm signal when there is an event of interest. The alarm signal can be used either to draw the event to the immediate attention of an operator, to place an index mark in recorded video or to trigger selective recording of CCTV data.
Some automatic event detectors have been developed for CCTV systems, though few of these are very successful. The most common devices are called video motion detectors (VMDs) or activity detectors, though they are generally based on simple algorithms concerning the detection of changes in the brightness of the video image—not the actual movement of imaged objects. For the purposes of detecting changes in brightness, the video image is generally divided into a grid of typically 16 blocks horizontally and vertically (i.e. 256 blocks in total). There several disadvantages of these algorithms. For example, they are prone to false alarms, for example when there are changes to the overall levels of illumination. Furthermore, they are unable to detect the movement of small objects, because of the block-based processing. In addition, they cannot be applied if the scene normally contains moving objects which are not of interest. These disadvantages can be reduced to a limited extent by additional processing logic, but the effectiveness of standard VMDs is inherently limited by the use of change detection as the initial image-processing stage.
There is another type of detection device, which is characterised by the use of complex algorithms involving image segmentation, object recognition and tracking and alarm decision rules. Though these devices can be very effective, they are generally expensive systems designed for use in specific applications and do not perform well without careful tuning and setting-up, and may not work at all outside of a limited range of applications for which they were originally developed.
U.S. Pat. No. 6,081,606 by inventors Wade & Jeffrey describes an apparatus and a method for detecting motion within an image sequence. That document discloses that motion within an image may be calculated by correlating areas of one image with areas of the next image in the video to generate a flow field. The flow field is then analysed and an alarm raised dependent on the observed magnitude and direction of flow.
European Patent No 0 986 912 describes a method for monitoring a predetermined surveillance region. A video image is divided into a number of segments. A statistical distribution for the mean grey level is determined for each segment. A change in mean grey level for a segment, outside the usual statistical variation, may be used to trigger an alarm.